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Fine-grained scalable sound representations for collaborative composition and performance

机译:细粒度的可伸缩声音表示形式,可实现协作创作和演奏

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Advances in processor technology have made it possible to use general-purpose computers as real-time digital signal processors in musical composition and multimedia applications. Real-time software synthesis and audio coding algorithms execute differently on different host hardware and operating systems. Our work explores the suitability of scalable sound representations for heterogeneous hosts and networks. The model we have developed is based on asynchronous granular synthesis. Two different representations are included in our model; an unbound granular model and a traditional grid-like structure. The first model allows the most flexibility for the composer, an almost unbound range of granular data of unlimited density can be used, and scheduling in the synthesiser decides which grains should be used at any one time. This is normally dependant on available computation time and the quality of output required by the application. The grid model was developed so that we could apply a similar level of real-time adaptation to natural sound signals. This paper concentrates on the design of a real-time asynchronous granular synthesis system, with scalability achieved through both real-time scheduling and continuously varying rendering quality. Experimental results are presented which show the behaviour of the synthesis system across a variety of hosts. Also presented is an analysis of how the extensive optimisation affects the audio quality in the synthesis system.
机译:处理器技术的进步使得在音乐创作和多媒体应用中将通用计算机用作实时数字信号处理器成为可能。实时软件综合和音频编码算法在不同的主机硬件和操作系统上以不同的方式执行。我们的工作探索了可扩展声音表示形式对异构主机和网络的适用性。我们开发的模型基于异步粒度综合。我们的模型中包含两种不同的表示形式;无约束的粒度模型和传统的网格状结构。第一个模型为作曲者提供了最大的灵活性,可以使用无限范围的无限密度的粒度数据,并且在合成器中进行调度可以决定一次应使用哪种颗粒。这通常取决于可用的计算时间和应用程序所需的输出质量。开发网格模型是为了使我们可以对自然声音信号应用类似级别的实时自适应。本文着重于实时异步粒度综合系统的设计,该系统具有通过实时调度和连续变化的呈现质量来实现的可伸缩性。实验结果表明,该合成系统在各种宿主之间的行为。还介绍了全面优化如何影响合成系统中音频质量的分析。

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